Update README.md
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README.md
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@@ -12,6 +12,92 @@ metrics:
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- rouge
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language:
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- en
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inference:
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parameters:
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max_length: 128
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- rouge
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language:
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- en
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examples:
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- text: |
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import torch
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from transformers import AutoTokenizer, AutoModelForSequenceClassification
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checkpoint = "distilbert-base-uncased-finetuned-sst-2-english"
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tokenizer = AutoTokenizer.from_pretrained(checkpoint)
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model = AutoModelForSequenceClassification.from_pretrained(checkpoint)
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sequences = ["I've been waiting for a HuggingFace course my whole life.", "So have I!"]
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tokens = tokenizer(sequences, padding=True, truncation=True, return_tensors="pt")
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output = model(**tokens)
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example_title: Example One
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- text: |
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import torch
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from tqdm.auto import tqdm
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device = torch.device("cuda") if torch.cuda.is_available() else torch.device("cpu")
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model.to(device)
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progress_bar = tqdm(range(num_training_steps))
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model.train()
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for epoch in range(num_epochs):
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for batch in train_dataloader:
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batch = {k: v.to(device) for k, v in batch.items()}
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outputs = model(**batch)
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loss = outputs.loss
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loss.backward()
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optimizer.step()
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lr_scheduler.step()
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optimizer.zero_grad()
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progress_bar.update(1)
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example_title: Example Two
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- text: |
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import evaluate
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metric = evaluate.load("glue", "mrpc")
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model.eval()
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for batch in eval_dataloader:
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batch = {k: v.to(device) for k, v in batch.items()}
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with torch.no_grad():
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outputs = model(**batch)
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logits = outputs.logits
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predictions = torch.argmax(logits, dim=-1)
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metric.add_batch(predictions=predictions, references=batch["labels"])
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metric.compute()
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example_title: Example Three
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- text: |
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git lfs install
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huggingface-cli lfs-enable-largefiles .
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git lfs track "*.bin"
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git add .
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git commit -a -m "add fp32 chkpt"
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git push
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example_title: Example Four
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- text: |
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export interface DocumentParams {
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pageContent: string;
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// eslint-disable-next-line @typescript-eslint/no-explicit-any
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metadata: Record<string, any>;
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}
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/**
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* Interface for interacting with a document.
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*/
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export class Document implements DocumentParams {
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pageContent: string;
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// eslint-disable-next-line @typescript-eslint/no-explicit-any
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metadata: Record<string, any>;
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constructor(fields?: Partial<DocumentParams>) {
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this.pageContent = fields?.pageContent ?? this.pageContent;
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this.metadata = fields?.metadata ?? {};
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}
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}
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example_title: Example Five
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inference:
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parameters:
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max_length: 128
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